We propose to develop a computational model of a complete cellular protein homeostasis (proteostasis) network, including protein synthesis, degradation, folding stability, aggregation, and competing/cooperating chaperoning systems. This project is a collaboration between Lila Gierasch (University of Massachusetts Amherst) and Evan Powers (The Scripps Research Institute). Our model, called FoldEco, aims to describe the balance of biochemical and physical aspects of folding and aggregation, and their impact on the health of the proteins in proteomes in general, and here the proteome of the E. coli cytoplasm, in particular. FoldEco begins with the current extensive knowledge of mechanisms, biochemical circuits, and parameters, and allows for the generation of hypotheses about large-scale, complex protein folding networks under various conditions. We propose now: (1) to advance FoldEco so that it better captures the full complexity of the E. coli proteome as well as physiological processes such as the heat-shock regulatory response that play a role in proteostasis in E. coli; (2) to experimentally interrogate E. coli proteostasis under physiological conditions in order to test and ultimately improve the FoldEco model. As part of our work, we will be addressing the burden placed on the proteome by perturbation of individual proteins, how well the proteostasis network copes with such perturbations, and whether some proteins are particularly vulnerable to such perturbations. We will continue to make the FoldEco model freely available to the broad community through a web-based interface. We already have the FoldEco code in a first generation version and several experimental tests of predictions of the code. Because chaperone networks are conserved across all organisms, this work in the simple model organism, E. coli, will provide insight into protein homeostasis in higher organisms and potentially assist in the development of therapeutic strategies for protein misfolding diseases. Additionally, FoldEco will benefit the biotechnological and pharmaceutical industries where the need to produce functional proteins efficiently is critical. If successful, this work will broadly advance our ability to comprehend complex circuits that play critical roles in health and disease.